News Article

  • 14 December 2015

    Meeting the demands of modern genomic studies

    For many leading genome labs getting access to more data has the capacity to improve the depth of their insights and analyses of individual and community responses to disease.

    Genomics continues to be an important element in the investigative tools used by researchers to improve our understanding of the impact of our genetic makeup on our responses to different diseases and treatment regimes.

    However, genomic labs across the world face similar challenges and these are:

    • the volumes and velocity of data created from gene sequences, and
    • the diversity of data sources researchers need to access and analyse.

    Often, as data volumes and types grow, researchers take more time manually searching archives, emails and databases to locate data they need to begin their work. Once located, researchers have to collate these data before the real work can begin. All of which takes valuable time that could be spent on analysing trends, testing hypotheses and gaining insights.

    So, leading researchers in Australia and internationally are using Mediaflux to improve the management and access to the rapidly increasing volumes of data generated from genomic studies.

    Now, once sequencing is complete, researchers use the powerful metadata extraction capabilities and workflow tools within Mediaflux to:

    • automatically extract key attributes about each study, such as the experiment number, sequencing techniques, individual phenotypes, and sample types,
    • immediately find out if the required files are online, or if they have been moved to lower cost storage, and
    • more quickly find and retrieve data they need so they can begin their real work.

    This means researchers can now hone in on the data they need in hours instead of days or even weeks. In this way, researchers are able to accelerate their efforts into devising solutions to some of the toughest biomedical problems we face today.

    The result is that researchers can now focus their attention on significant research, rather than data wrangling.